Multilinear Subspace Learning For Face And Gait Recognition
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Multilinear Subspace Learning For Face And Gait Recognition
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Author : Haiping Lu
language : en
Publisher:
Release Date : 2008
Multilinear Subspace Learning For Face And Gait Recognition written by Haiping Lu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Face and gait recognition problems are challenging due to largely varying appearances, highly complex pattern distributions, and insufficient training samples. This dissertation focuses on multilinear subspace learning for face and gait recognition, where low-dimensional representations are learned directly from tensorial face or gait objects.This research introduces a unifying multilinear subspace learning framework for systematic treatment of the multilinear subspace learning problem. Three multilinear projections are categorized according to the input-output space mapping as: vector-to-vector projection, tensor-to-tensor projection, and tensor-to-vector projection. Techniques for subspace learning from tensorial data are then proposed and analyzed. Multilinear principal component analysis (MPCA) seeks a tensor-to-tensor projection that maximizes the variation captured in the projected space, and it is further combined with linear discriminant analysis and boosting for better recognition performance. Uncorrelated MPCA (UMPCA) solves for a tensor-to-vector projection that maximizes the captured variation in the projected space while enforcing the zero-correlation constraint. Uncorrelated multilinear discriminant analysis (UMLDA) aims to produce uncorrelated features through a tensor-to-vector projection that maximizes a ratio of the between-class scatter over the within-class scatter defined in the projected space. Regularization and aggregation are incorporated in the UMLDA solution for enhanced performance.Experimental studies and comparative evaluations are presented and analyzed on the PIE and FERET face databases, and the USF gait database. The results indicate that the MPCA-based solution has achieved the best overall performance in various learning scenarios, the UMLDA-based solution has produced the most stable and competitive results with the same parameter setting, and the UMPCA algorithm is effective in unsupervised learning in low-dimensional subspace. Besides advancing the state-of-the-art of multilinear subspace learning for face and gait recognition, this dissertation also has potential impact in both the development of new multilinear subspace learning algorithms and other applications involving tensor objects.
Multilinear Subspace Learning
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Author : Haiping Lu
language : en
Publisher: CRC Press
Release Date : 2013-12-11
Multilinear Subspace Learning written by Haiping Lu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Computers categories.
Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional techniques. Addressing this need, multilinear subspace learning (MSL) reduces the dimensionality of big data directly from its natural multidimensional representation, a tensor. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. It covers the fundamentals, algorithms, and applications of MSL. Emphasizing essential concepts and system-level perspectives, the authors provide a foundation for solving many of today’s most interesting and challenging problems in big multidimensional data processing. They trace the history of MSL, detail recent advances, and explore future developments and emerging applications. The book follows a unifying MSL framework formulation to systematically derive representative MSL algorithms. It describes various applications of the algorithms, along with their pseudocode. Implementation tips help practitioners in further development, evaluation, and application. The book also provides researchers with useful theoretical information on big multidimensional data in machine learning and pattern recognition. MATLAB® source code, data, and other materials are available at www.comp.hkbu.edu.hk/~haiping/MSL.html
Advanced Signal Processing
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Author : Stergios Stergiopoulos
language : en
Publisher: CRC Press
Release Date : 2017-09-29
Advanced Signal Processing written by Stergios Stergiopoulos and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-29 with Technology & Engineering categories.
Discover the Applicability, Benefits, and Potential of New Technologies As advances in algorithms and computer technology have bolstered the digital signal processing capabilities of real-time sonar, radar, and non-invasive medical diagnostics systems, cutting-edge military and defense research has established conceptual similarities in these areas. Now civilian enterprises can use government innovations to facilitate optimal functionality of complex real-time systems. Advanced Signal Processing details a cost-efficient generic processing structure that exploits these commonalities to benefit commercial applications. Learn from a Renowned Defense Scientist, Researcher, and Innovator The author preserves the mathematical focus and key information from the first edition that provided invaluable coverage of topics including adaptive systems, advanced beamformers, and volume visualization methods in medicine. Integrating the best features of non-linear and conventional algorithms and explaining their application in PC-based architectures, this text contains new data on: Advances in biometrics, image segmentation, registration, and fusion techniques for 3D/4D ultrasound, CT, and MRI Fully digital 3D/ (4D: 3D+time) ultrasound system technology, computing architecture requirements, and relevant implementation issues State-of-the-art non-invasive medical procedures, non-destructive 3D tomography imaging and biometrics, and monitoring of vital signs Cardiac motion correction in multi-slice X-ray CT imaging Space-time adaptive processing and detection of targets interference-intense backgrounds comprised of clutter and jamming With its detailed explanation of adaptive, synthetic-aperture, and fusion-processing schemes with near-instantaneous convergence in 2-D and 3-D sensors (including planar, circular, cylindrical, and spherical arrays), the quality and illustration of this text’s concepts and techniques will make it a favored reference.
Adversarial Machine Learning
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Author : Aneesh Sreevallabh Chivukula
language : en
Publisher: Springer Nature
Release Date : 2023-03-06
Adversarial Machine Learning written by Aneesh Sreevallabh Chivukula and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-06 with Computers categories.
A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical adversarial deep learning algorithms. The state-of-the-art in adversarial perturbation-based privacy protection mechanisms is also reviewed. We propose new adversary types for game theoretical objectives in non-stationary computational learning environments. Proper quantification of the hypothesis set in the decision problems of our research leads to various functional problems, oracular problems, sampling tasks, and optimization problems. We also address the defence mechanisms currently available for deep learning models deployed in real-world environments. The learning theories used in these defence mechanisms concern data representations, feature manipulations, misclassifications costs, sensitivity landscapes, distributional robustness, and complexity classes of the adversarial deep learning algorithms and their applications. In closing, we propose future research directions in adversarial deep learning applications for resilient learning system design and review formalized learning assumptions concerning the attack surfaces and robustness characteristics of artificial intelligence applications so as to deconstruct the contemporary adversarial deep learning designs. Given its scope, the book will be of interest to Adversarial Machine Learning practitioners and Adversarial Artificial Intelligence researchers whose work involves the design and application of Adversarial Deep Learning.
Audio And Video Based Biometric Person Authentication
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Author : Takeo Kanade
language : en
Publisher: Springer
Release Date : 2011-04-06
Audio And Video Based Biometric Person Authentication written by Takeo Kanade and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-06 with Computers categories.
This book constitutes the refereed proceedings of the 5th International Conference on Audio- and Video-Based Biometric Person Authentication, AVBPA 2005, held in Hilton Rye Town, NY, USA, in July 2005. The 66 revised oral papers and 50 revised poster papers presented were carefully reviewed and selected from numerous submissions. The papers discuss all aspects of biometrics including iris, fingerprint, face, palm print, gait, gesture, speaker, and signature; theoretical and algorithmic issues are dealt with as well as systems issues. The industrial side of biometrics is evident from presentations on smart cards, wireless devices, and architectural and implementation aspects.
Multimedia Analysis Processing And Communications
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Author : Lin Weisi
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-11
Multimedia Analysis Processing And Communications written by Lin Weisi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-11 with Mathematics categories.
This book has brought 24 groups of experts and active researchers around the world together in image processing and analysis, video processing and analysis, and communications related processing, to present their newest research results, exchange latest experiences and insights, and explore future directions in these important and rapidly evolving areas. It aims at increasing the synergy between academic and industry professionals working in the related field. It focuses on the state-of-the-art research in various essential areas related to emerging technologies, standards and applications on analysis, processing, computing, and communication of multimedia information. The target audience of this book is researchers and engineers as well as graduate students working in various disciplines linked to multimedia analysis, processing and communications, e.g., computer vision, pattern recognition, information technology, image processing, and artificial intelligence. The book is also meant to a broader audience including practicing professionals working in image/video applications such as image processing, video surveillance, multimedia indexing and retrieval, and so on. We hope that the researchers, engineers, students and other professionals who read this book would find it informative, useful and inspirational toward their own work in one way or another.
Local Binary Patterns New Variants And Applications
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Author : Sheryl Brahnam
language : en
Publisher: Springer
Release Date : 2013-09-01
Local Binary Patterns New Variants And Applications written by Sheryl Brahnam and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-01 with Technology & Engineering categories.
This book introduces Local Binary Patterns (LBP), arguably one of the most powerful texture descriptors, and LBP variants. This volume provides the latest reviews of the literature and a presentation of some of the best LBP variants by researchers at the forefront of textual analysis research and research on LBP descriptors and variants. The value of LBP variants is illustrated with reported experiments using many databases representing a diversity of computer vision applications in medicine, biometrics, and other areas. There is also a chapter that provides an excellent theoretical foundation for texture analysis and LBP in particular. A special section focuses on LBP and LBP variants in the area of face recognition, including thermal face recognition. This book will be of value to anyone already in the field as well as to those interested in learning more about this powerful family of texture descriptors.
Data Management And Statistical Analysis Techniques
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Author : Ronin Myers
language : en
Publisher: Scientific e-Resources
Release Date : 2019-05-19
Data Management And Statistical Analysis Techniques written by Ronin Myers and has been published by Scientific e-Resources this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-19 with categories.
Eigenface
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2024-05-14
Eigenface written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-14 with Computers categories.
What is Eigenface An eigenface is the name given to a set of eigenvectors when used in the computer vision problem of human face recognition. The approach of using eigenfaces for recognition was developed by Sirovich and Kirby and used by Matthew Turk and Alex Pentland in face classification. The eigenvectors are derived from the covariance matrix of the probability distribution over the high-dimensional vector space of face images. The eigenfaces themselves form a basis set of all images used to construct the covariance matrix. This produces dimension reduction by allowing the smaller set of basis images to represent the original training images. Classification can be achieved by comparing how faces are represented by the basis set. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Eigenface Chapter 2: Principal component analysis Chapter 3: Singular value decomposition Chapter 4: Eigenvalues and eigenvectors Chapter 5: Eigendecomposition of a matrix Chapter 6: Kernel principal component analysis Chapter 7: Matrix analysis Chapter 8: Linear dynamical system Chapter 9: Multivariate normal distribution Chapter 10: Modes of variation (II) Answering the public top questions about eigenface. (III) Real world examples for the usage of eigenface in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Eigenface.
Behavioral Biometrics For Human Identification Intelligent Applications
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Author : Wang, Liang
language : en
Publisher: IGI Global
Release Date : 2009-08-31
Behavioral Biometrics For Human Identification Intelligent Applications written by Wang, Liang and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-31 with Computers categories.
"This edited book provides researchers and practitioners a comprehensive understanding of the start-of-the-art of behavioral biometrics techniques, potential applications, successful practice, and available resources"--Provided by publisher.